Update mentoring.md

tracks/python/exercises/perfect-numbers/mentoring.md

@@ -29,7 +29,7 @@ A simple optimization is to use `range(1, number // 2 + 1)` as the `for` loop `i
 This halves the complexity of the solution.
 
 For a more efficient solution, one can compute all the factors by using the smaller `range(1, int(math.sqrt(number)) + 1)` as the `iterable`.
-This solution is longer and more involved but significantly faster, reducing the complextiy from `O(n)` (_linear_) to `O(sqrt(n))` (_square root_).
+This solution is longer and more involved but significantly faster, reducing the complexity from `O(n)` (_linear_) to `O(sqrt(n))` (_square root_).
 
 ```python
 def classify(number):
@@ -49,5 +49,5 @@ def classify(number):
 
 Students unfamiliar with `generator expressions` might write: `aliquot = sum([item for item in range(1, number) if number % item == 0])`.
 Note this first creates a `list` of factors in memory by iterating over the entire range, then iterates once more over the `list` to `sum()` its values.
-This is inefficent for both memory and processing time.
-Dropping the `[]` drops `list` creation and allows `sum()` to lazily process a `generator expression`, wich only requires a single iteration and a smaller memory footprint.
+This is inefficient for both memory and processing time.
+Dropping the `[]` drops `list` creation and allows `sum()` to lazily process a `generator expression`, which only requires a single iteration and a smaller memory footprint.